This paper develops a general model that addresses the starting point bias in the dichotomous choice evaluation data by incorporating both the anchoring effect and yea-saying bias. The model is applied to a contingent valuation study that evaluated the health benefits of air quality improvement...

Heckman’s (1976, 1979) sample selection model has been employed in many studies of linear or nonlinear regression applications. It is well known that ignoring the sample selectivity problem may result in inconsistency of the estimator due to the correlation between the statistical errors in...

A simple approximation for the bivariate normal cumulative distribution function (BNCDF) based on the error function is derived. The worst error of our method is found to four decimal places under various configurations considered in this paper's Table 1. This finding is much better than that in...

This paper investigates the time to first birth, treating coresidence with husband's parents and labor supply as endogenous and using representative data on Taiwanese married women born over 1933-1968. We utilize a full information maximum likelihood estimator for a duration model with...

It is found in Lee (2000) and Rabe-Hesketh et al. (2005) that the typical numerical-integral procedure suggested by Butler and Moffitt (1982) for the random effects probit model becomes biased when the correlation coefficient within each unit is relatively large. This could possibly explain why...

This paper presents a generalized autoregressive distributed lag (GADL) model for conducting regression estimations that involve mixed-frequency data. As an example, we show that daily asset market information - currency and equity mar- ket movements - can produce forecasts of quarterly...

This paper derives an analytic approximation formula for the likelihood function of the true random effects stochastic frontier model of Greene (2005) with a time span T = 2. Gaussian quadrature procedure and simulation-based method is not re- quired for the closed-form approach. Combining the...